Abstract
Hybrid energy systems are considered to be an appropriate solution for sustainable and clean energy supply. Due to the variability of energy amounts that can be generated by using renewable resources, energy intermittencies and voltage fluctuations may occur in these systems. Placement of energy storage units into hybrid energy systems are suggested to overcome the mentioned problems. There are several types of energy storage units at different technical conditions and prices, and consideration of several criteria simultaneously makes the selection of the most appropriate unit a multiple-criteria decision making problem. Moreover, evaluation of decision elements is usually not possible with precise quantitative values and decision makers sometimes feel hesitant on the assessment of decision elements. The main aim of this study is to propose a group decision making model based on Hesitant Fuzzy Linguistic Terms Set to determine the most appropriate energy storage unit in hybrid energy systems to overcome the aforementioned difficulties. Energy storage unit selection criteria were determined by a literature review, then criteria evaluation of experts were collected and the importance degree of each criterion was determined by pairwise comparisons. The obtained results of the study would support storage unit investment decisions in hybrid energy systems.
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Acknowledgements
Ahmet Aktas was a visiting researcher at University of Coimbra during a part of this study. The author acknowledges the support of the Scientific and Technological Research Council of Turkey (TUBITAK-2214-A program).
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Aktas, A., Kabak, M. (2021). A Hesitant Fuzzy Linguistic Group Decision Making Model for Energy Storage Unit Selection. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I., Cebi, S., Tolga, A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197. Springer, Cham. https://doi.org/10.1007/978-3-030-51156-2_32
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DOI: https://doi.org/10.1007/978-3-030-51156-2_32
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